Behçet syndrome: The disturbed balance between anti‐ (CLEC12A, CLC) and proinflammatory (IFI27) gene expressions

Abstract Introduction Behçet syndrome (BS) is a chronic, multisystemic inflammatory condition with unanswered questions regarding its pathogenesis and rational therapeutics. A microarray‐based comparative transcriptomic analysis was performed to elucidate the molecular mechanisms of BS and identify any potential therapeutic targets. Methods Twenty‐nine BS patients (B) and 15 age and sex‐matched control subjects (C) were recruited. Patients were grouped as mucocutaneous (M), ocular (O), and vascular (V) according to their clinical phenotypes. GeneChip Human Genome U133 Plus 2.0 arrays were used for expression profiling on peripheral blood samples of the patients and the control subjects. Following documentation of the differentially expressed gene (DEG) sets, the data were further evaluated with bioinformatics analysis, visualization, and enrichment tools. Validation of the microarray data was performed using quantitative reverse transcriptase polymerase chain reaction. Results When p ≤ 0.05 and fold change ≥2.0 were chosen, the following numbers of DEGs were obtained; B versus C: 28, M versus C: 20, O versus C: 8, V versus C: 555, M versus O: 6, M versus V: 324, O versus V: 142. Venn diagram analysis indicated only two genes, CLEC12A and IFI27, in the intersection of M versus C ∩ O versus C ∩ V versus C. Another noteworthy gene appeared as CLC in the DEG sets. Cluster analyses successfully clustered distinct clinical phenotypes of BS. While innate immunity‐related processes were enriched in the M group, adaptive immunity‐specific processes were significantly enriched in the O and V groups. Conclusions Distinct clinical phenotypes of BS patients displayed distinct expression profiles. In Turkish BS patients, expression differences regarding the genes CLEC12A, IFI27, and CLC seemed to be operative in the disease pathogenesis. Based on these findings, future research should consider the immunogenetic heterogeneity of BS clinical phenotypes. Two anti‐inflammatory genes, namely CLEC12A and CLC, may be valuable as therapeutic targets and may also help design an experimental model in BS.


| Approval of the ethics committee, centers participating in the study, and selection of patients with BS and control group individuals
The Ethics Committee of Ufuk University (Ankara, Turkey) approved the study with decision number 08065 dated 06. 24.2009.
The BS patients included in this study consisted of BS cases visiting the outpatient clinics of Ufuk University Faculty of Medicine Department of Dermatology, Ankara University Faculty of Medicine Division of Rheumatology, and Ankara Numune Training and Research Hospital Rheumatology Clinic, for their routine follow-up visits, who fulfilled the International Study Group for Behçet's Disease criteria for diagnosis of Behçet's disease and agreed to participate in the study by signing the relevant, informed consent form. 8 BS patients with a current exacerbation of their disease other than a mucocutaneous involvement, a concomitant second inflammatory disorder, and any concurrent infectious or malignant diseases were excluded from the study.
The control group individuals included in the study were chosen to be compatible with the BS group regarding their age and gender. They were selected among individuals visiting Ufuk University Faculty of Medicine hospital checkup outpatient clinics, who were in absolutely good health, did not report any complaints consistent with an infectious or inflammatory disorder, did not have any current or past significant health issues, did not demonstrate any abnormal physical exam and laboratory findings, did not have a personal history of BS or a BS history in their families, and agreed to participate in the study by signing the relevant, informed consent form.

| Collection of the blood samples and obtaining the clinical information of BS patients and control group individuals
Blood samples of BS patients and control group individuals were collected using PAXgene® Blood RNA Tube (Pre-AnalytiX®; Catalog no: 762165). A total of two tubes (samples) were obtained from each BS case and each control group individual included in the study, one for use during the study and the other as a precautionary measure. The blood samples collected were preserved at room temperature for the first 24 h, at −20°C for the next 24 h, and then at −80°C until the day they were to be analyzed, following the manufacturer's protocol (PAXgene® Blood RNA Tube Handbook).
The relevant clinical information of the BS cases and the control group individuals included in the study were obtained using the specifically designed "Case Report Form" (Supporting Information: 1 File). Because of major medical and ethical considerations, BS cases enrolled did not discontinue their current medications during the study.

| Description of BS clinical phenotypes
The BS patients included in the study were grouped into four clinical phenotypes as mucocutaneous BS (M), ocular BS (O), vascular BS (V), and other BS (D) according to their individual clinical characteristics and the criteria presented in Table 1. 5,[9][10][11][12][13] 2.4 | Statistical analysis of key demographic characteristics As the demographic data of the study did not follow a normal distribution, the median as a measure of central tendency together with the minimum and maximum values, and the Mann−Whitney U and the χ 2 tests to compare two independent groups were used. The p values of the analyses were presented with their absolute numerical values, and a p ≤ 0.05 was considered statistically significant. Statistical analyses of the demographic data were performed using "SPSS for Windows, Version 16.0" software (SPSS Inc. Released 2007. SPSS for Windows; Version 16.0.; SPSS Inc.).

| RNA isolation and purification from peripheral whole blood samples
The flowchart summarizing the in vitro experiments of the study is presented in Figure 1.
RNA isolation & purification from blood samples collected for the study were performed using the PAXgene® Blood RNA Kit (PreAnalytiX®; Catalog no: 762174). Following the manufacturer's protocol, the tubes removed from the freezer just before the RNA isolation process were first equilibrated to room temperature and then kept at room temperature for an additional 2 h. All steps of the RNA isolation & purification process were performed in complete adherence to the protocol recommended by the manufacturer's, as described in the PAXgene® Blood RNA Kit Handbook. For every purified RNA sample, a 500 ng amount required for the downstream analysis was stored at −80°C, in addition to aliquots for RNA quantity/quality analyses and stocking purposes.

| RNA quantity and quality analyses
The RNA samples isolated were run and evaluated in a 1% agarose gel. A260 and A280 values were measured using a nano-spectrophotometer (NanoDrop® 2000/2000c Spectrophotometer; Thermo Fisher Scientific®). Consequently, they Other BS In addition to mucocutaneous findings, there is ocular involvement and/or vascular involvement and/or musculoskeletal involvement and/or gastrointestinal system involvement and/or nervous system involvement. Catalog no: 00-0079), using the relevant components in the "GeneChip® Hybridization, Wash, and Stain Kit" (Applied Biosystems®; Catalog no: 900720). Again, the protocol defined by the manufacturer's was precisely followed for this step (GeneChip® Expression Analysis Technical Manual). Consequent to the washing & staining steps, the microarrays were transferred to and scanned on the "GeneChip® Scanner 3000" (Applied Biosystems®; Catalog no: 00-0186) by using the "Affymetrix,® GeneChip® Command Console® 4.0" (AGCC) software. Upon completion of the scanning process, the AGCC software generated ".dat" and ".cel" files along with ".exp," ".chp," and ".rpt" files. Among these files, the.dat file contained the scanned microarray image, and the.cel file contained the light intensity (brightness) values of each probe set, defined by a grid. For the downstream bioinformatics analyses, these raw.cel files were used.

| Quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) validation experiments for expression levels of selected genes
Validation experiments of this hybridization-based expression study were performed using qRT-PCR. For this purpose, the first 12 genes presented in the first column of Table 2 were selected, considering their fold change (FC) values, and potential significance to molecular disease mechanisms of BS. An effort was made to keep an absolute FC value of ≥3 for the genes to be selected. Based on the relevant literature, the peptidylprolyl isomerase B gene (PPIB) was chosen as the "housekeeping" gene. 14 Validation qRT-PCR experiments were performed on a "LightCycler® 480" (Roche Applied Science®; Catalog no: 05 015 278 001) thermocycler, with 10 samples selected from each of the mucocutaneous BS, vascular BS, and healthy control groups. Each sample was run in triplicates. Details of the "RealTime Ready® Catalog Assays" (Roche Applied Science®; Catalog no: 05 532 957 001) primers used during the experiments are also given in Table 2. "LightCycler® 480 Probes Master" (Roche Applied Science®; Catalog no: 04 707 494 001) was used to prepare the reaction medium, and the reaction setup was carried out following the protocol recommended by the manufacturer's. The "Delta-Delta-Ct" (ddCt) algorithm was used to calculate the qRT-PCR-based expression levels. 15

| Preprocessing of the microarray data
The metadata, raw, and final/normalized data of the study are deposited to the GEO repository (accession: GSE209567, date: 7.22.2022). The flowchart summarizing the bioinformatics analyses of the study is presented in Figure 3. The collation and all of the preprocessing steps of the microarray data were conducted using the "BRB-ArrayTools v4.4.1 Stable release" developed by Dr. Richard Simon and the "BRB-ArrayTools" development team (https://brb.nci. nih.gov/BRB-ArrayTools/). Initially, the raw microarray data existing as individual.cel files were collated using the data import function of the "BRB-ArrayTools" software. Normalization of the imported microarray data was performed using the "Robust Multiarray Average" algorithm, which includes (1) background correction, (2) binary logarithmic transformation, and (3) quantile normalization. 16 Following this normalization step, the replicate probe sets were averaged. Finally, gene filters were implemented, which helped to exclude genes that are not likely to be informative. For this purpose, a "minimum fold-change filter" in addition to a "percent missing filter" were used, which were ready-to-use functions of the "BRB-ArrayTools" software.

| Bioinformatics analyses of the gene expression data
Class comparison analyses were performed using the "BRB-ArrayTools v4.4.1" software (https://brb.nci.nih.gov/BRB-ArrayTools/). For the class comparison analyses, a twosample t-test with a random variance model was implemented. The p value was chosen as ≤0.05 and the FC value as ≥2. For certain occasions, where a greater number of differentially expressed genes (DEG) are a prerequisite for optimal results (e.g., gene set enrichment analysis), an FC value ≥1.5 was also additionally used. The Venn diagram analysis of the findings of the class comparisons was performed with "Venny 2.1.0" developed by Juan Carlos Oliveros (https://bioinfogp.cnb.csic.es/tools/venny/).
For clustering analyses of BS cases, the built-in clustering tools of "BRB-ArrayTools" software and "Cluster 3.0" and the "TreeView" software packages were used (http://bonsai.hgc.jp/~mdehoon/software/ cluster/software.htm#ctv). 17 During the clustering analyses, both cases and genes were clustered together, and a hierarchical clustering algorithm using Gene ontology (GO) term enrichment analyses of the DEG sets were performed using the "WEB-based Gene Set Analysis Toolkit" (WebGestalt) and specifically focused on the sub-title of biological processes. 18,19 DEG sets obtained during M versus C, O versus C, and V versus C class comparisons were used for GO term enrichment analyses. The setup for the GO term enrichment analyses consisted of the hypergeometric test, the Benjamini−Hochberg correction for multiple comparison adjustment, and two as the minimum number of genes in a category.

| Key demographics of the BS patients and the control subjects
The essential demographic characteristics of the BS patients and the control subjects are presented in Table 3. The groups B and C were similar with respect to their ages and genders.

| Detailed demographic and clinical characteristics of the study group
The detailed demographic and clinical characteristics of the BS cases and the control subjects included in the study are presented in Table 4 (Supporting Information: 4 File). The group D (other BS) patients (D1−D7) were excluded from further analyses, due to their divergent clinical phenotypes, small sample sizes, and the study design.

| Number of probe sets used during comparative expression analyses
Following the preprocessing steps performed on the collated 44.cel files, 10,785 probe sets out of the 54,675 present on the "GeneChip® Human Genome U133 Plus 2.0" microarrays, passed the adjusted filters and were used during the subsequent bioinformatics analyses.

| Findings of the class comparison analyses
Details regarding the number of the DEGs obtained during the class comparison analyses are shown in Table 5 (Supporting Information: 5 File).
The top 20 (10 increased and 10 decreased) most differentially expressed genes, obtained by the class comparison analyses of the BS patient subgroups with the control group, are listed according to their FC values and presented in Table 6. Complete lists of the DEG sets can be found in the Supporting Information: 5 File. The IFI27 and CLEC12A genes which were the only two common genes in the DEG sets of the class comparisons M versus C, O versus C, and V versus C, were also among the top three most differentially expressed genes in these comparisons, specifically when the interfering sex chromosome genes were excluded from the list.
The Venn analysis diagram of the DEG sets obtained during class comparison analyses between the BS patient subgroups and the control group is shown in Figure 4.

| Findings of the clustering analyses of BS patient subgroups
The dendrogram and heatmap representations of clustering analyses performed among subgroups of patients with BS are presented in Figure 5. The clustering algorithm implemented, successfully clustered the BS cases in nearly perfect agreement with their clinical phenotypes. Complete lists of the DEG sets used during clustering analyses can be found in the Supporting Information: 6 File.

| Findings of the GO enrichment analyses
Selected findings of the GO enrichment analyses, performed using the DEG sets of the class comparisons M versus C, O versus C, and V versus C, are presented in Table 7 (details regarding the GO term enrichment analyses are given in Supporting Information: 7 File). While innate immunity and hemostasis-related biological processes were significantly enriched in the M group, adaptive immunity-specific biological processes were more prominently enriched in the O and V groups.

| Findings of the validation experiments
The findings of the validation experiments, performed using a qRT-PCR approach, are presented in Table 8. For the selected 12 genes, the qRT-PCR findings of the validation experiments performed were consistent with the microarray findings. Not only the direction of change, but also the amplitude of change were compatible in many instances (Table 8).

| DISCUSSION
This study performed a comparative genome-wide expression analysis of Turkish BS patients, using a novel study design that differentiated it from other similar studies in the relevant literature. 7,20-24 Based on the  At the beginning of the discussion and before going deep in dissection of the findings, the authors of the study emphasize that the approach of collecting and studying distinct BS clinical phenotypes as a single group, may unintentionally lead to loss of important information, especially at the molecular level. In other words, as the authors we believe that, the study design has a significant impact on the findings of BS studies.
The combined gene-expression profiling and genomewide association study by Xavier et (2) different molecular disease mechanisms seem to be functional in different disease expressions of BS, and (3) four functionally related gene groups, namely, negative regulators of inflammation (CD69, CLEC12A, CLEC12B, TNFAIP3), neutrophil granule proteins (LTF, OLFM4, AZU1, MMP8, DEFA4, CAMP), antigen processing and presentation proteins (CTSS, ERAP1), and regulators of immune response (LGALS2, BCL10, ITCH, CEACAM8, CD36, IL8, CCL4, EREG, NFKBIZ, CCR2, CD180, KLRC4, NFAT5) appear to be instrumental in BS immunopathogenesis. 5 Based on their findings, Oguz et al. concluded that, the designation as "Behçet syndrome" should be encouraged and future research should take into consideration the immunogenetic heterogeneity of BS clinical phenotypes. 5 Interestingly, CLEC12A which appeared in the "negative regulators of inflammation" gene group of Oguz et al., was also a significant finding of the present study. 5 Two innate immune response genes drew special attention, namely CLEC12A and IFI27 in the DEG sets of the class comparisons M versus C, O versus C, and V versus C. Besides their potential functional significance in BS pathogenesis, CLEC12A and IFI27 both were among the top 10 DEGs (Table 6). Table 9 presents the FC values of these two genes, obtained by the BS subgroup versus control group class comparisons. Strikingly, also during the Venn analysis, CLEC12A and IFI27 were found to be the only two genes present in the intersection M versus C ∩ O versus C ∩ V versus C ( Figure 4). CLEC12A (C-type lectin domain family 12 member A, also known as MICL, KLRL1, CD371) is an innate immune system receptor, expressed on the surface of granulocytes, monocytes/macrophages, and NK lymphocytes with an inhibitory function. 25,26 It appears that CLEC12A exerts its inhibitory effect via the immunoreceptor tyrosine-based inhibitor motif (ITIM) present on its cytoplasmic tail. 25,26 CLEC12A, of which uric acid crystals have been shown as one of its endogenous ligands, is thought to have an important role in regulating the immune response and maintaining homeostasis by reducing the severity of the inflammatory reaction, especially in the presence of tissue injury. [27][28][29] As an important finding, it has been reported that the anti-inflammatory agent colchicine, which is currently prescribed for the treatment of BS, gout, and Familial Mediterranean Fever all of which are neutrophilmediated inflammatory diseases, induces the expression of CLEC12A. 30 Studies of rheumatoid arthritis (RA) have also shown that, loss of CLEC12A function or its decreased expression is associated with an increased RA disease activity and inflammation severity. [31][32][33] Oguz et al., after noticing the decreased expression of CLEC12A in Turkish BS cases during preliminary analysis of their transcriptome data and by collecting the findings in the literature on CLEC12A, proposed the hypothesis that CLEC12A may be a common denominator in the development of BS and gout. 34 In support of their hypothesis, Oguz et al. pointed to the findings of (1) negative correlation of CLEC12A expression with hyperinflammatory responses, (2) the presence of CLEC12A polymorphisms with functional and clinical effects in certain inflammatory diseases, (3) the dual use of colchicine for the treatment of BS and gout, (4) the exaggerated inflammatory response to uric acid crystals detected in both BS and gout cases, (5) the presence of the genomic locus of the CLEC12A gene (i.e., 12p12-13), among the findings of the GWAS and GWLS of BS, and (6) their preliminary finding of decreased CLEC12A expression in Turkish BS cases. 34 At the end of their hypothesis article, Oğuz et al. stated that, if their hypothesis about CLEC12A is proved with welldesigned studies in the future, scientists may be able to go a long way toward the elucidation of the pathogenesis of BS & gout, and also an animal model development for BS. 34 In a more recent review, French researcher Elise Chiffoleau emphasized that, C-type lectin-like receptors, including CLEC12A, could be potential treatment targets by playing important roles in the regulation of sterile inflammation. 35 Another recent research by Paré et al. documented the early molecular events by which CLEC12A inhibit neutrophil activation and cytokine release. 36 An important point to emphasize here is, CLEC12A ranked among the top 10 DEGs of the class comparisons M versus C and O versus C. When the Y chromosome genes (interfering as a result of the male/ female ratio discrepancy of the compared classes) are excluded from the M versus C list, CLEC12A becomes the most downregulated gene in both of the M versus C and O versus C class comparisons (Table 6). We believe that, all of these findings presented in a summarized manner support that, decreased expression of CLEC12A, which is a common finding in different clinical phenotype clusters of Turkish BS patients may have a role in the development of already well-documented exaggerated neutrophil functions and hyperinflammatory innate immune response in BS patients.
IFI27 (interferon alpha inducible protein 27, also known as P27, ISG12, FAM14D) is one of the genes belonging to the group of interferon-stimulated genes (ISG), mediating the antiviral, immunomodulatory, and antiproliferative effects of interferons. 37 During the years following their first description, interferon molecules were believed to be an important component of the innate immune system and its response against viruses due to their powerful antiviral effects. Today, interferons and ISGs that mediate their biological effects, are considered to function in both innate and adaptive arms of the immune system, and are thought to have important roles in the development of the close communication and cooperation between these two T A B L E 9 The fold change values of CLEC12A and IFI27 genes in BS subgroup versus control group class comparisons. inseparable components of the immune system. 38,39 The literature harbors many inflammatory/immunological conditions including inflammatory bowel diseases, psoriasis, systemic lupus erythematosus, Sjögren's syndrome, antiphospholipid syndrome, acute graft-versushost disease, immune thrombocytopenic purpura, Aicardi−Goutieres syndrome, Kikuchi−Fujimoto, and hand, foot, and mouth diseases, in which significant increases in IFI27 expression have been reported. [39][40][41][42][43][44][45][46][47][48][49][50] It is also well-known that, some of these above-mentioned inflammatory diseases (i.e., inflammatory bowel diseases, psoriasis, and systemic lupus erythematosus) have an intersection with BS. [51][52][53] Regarding interferons in BS, Belguendouz et al. reported an increased in vivo and in vitro production of interferon gamma in active ocular BS patients compared to inactive patients and healthy controls. 54 Additionally in the same study, interferon gamma was shown to induce nitric oxide production in vitro. 54 Based on their findings, Belguendouz et al. concluded that, interferon gamma was implicated in the occurrence of the inflammatory process of Behçet uveitis. 54 Similar to CLEC12A, IFI27 is also among the top 10 most DEG of the class comparisons (second in M vs. C with an FC: 3.49, second in O vs. C with an FC: 2.14, and third in V vs. C with an FC: 4.34) ( Table 6). As a remarkable and contradictory finding of the genomewide expression study of BS by Okuzaki et al., IFI27 was reported to be among the DEGs with a decreased expression in the patient (i.e., BS) group. 21 This contrasting situation may be noted as another good example of the discordant immunological findings observed in BS studies. Even though the association of increased IFI27 expression with inflammatory conditions has been consistently documented, the mechanisms underlying this finding remain to be clarified (i.e., whether IFI27 has a direct role here or IFI27 merely represents the presence of an innate immune proinflammatory cytokine response including the interferons). Another gene that drew attention in the class comparisons of the ocular and vascular BS groups with the control group was CLC. As is presented in Table 6, CLC ranked second with an FC of −2.57 for O versus C and 7th with an FC of −3.57 for V versus C class comparisons. CLC (Charcot−Leyden crystal protein, also known as GAL10, LGALS10) has historically been identified as an important component of human eosinophil leukocytes and is named after the Charcot−Leyden crystals, which are frequently observed at sites of eosinophilic inflammation. 55 CLC, which was thought to have lysophospholipase function for a long period of time, is now accepted as a member of the galectin (lectin) gene family. 56 CLC, with a primary carbohydrate affinity for mannose, is shown to play a role in immune system surveillance against inflammation and tumors. 57 59 According to the study findings of Kubach et al., CLC is highly expressed in CD4 + CD25 + regulatory T cell (Treg cell) cytoplasm, and this expression seems to be essential for the adaptive immune response suppressive functions of the regulatory T lymphocytes. 59 In the same study, specific inhibition of the CLC protein in regulatory T lymphocyte cytoplasm resulted in loss of regulatory T lymphocyte suppressor function. 59 In a more recent study, Lingblom et al. showed that CD16 + (high expression) eosinophil granulocyte population suppressed T lymphocyte functions via CLC. 60 Taken together with these literature information, our findings regarding decreased expression of CLC in the ocular and vascular BS subgroups may indicate that, in addition to CLEC12A and IFI27, CLC may also be playing a role in (1) the emergence of the characteristic hyperinflammatory manifestations of BS, and (2) the addition of the adaptive immune response to the initial scene of innate immunity in BS, particularly in ocular and vascular cases.

Gene
Mucocutaneous findings (i.e., recurrent oral and genital aphthae, various inflammatory skin lesions, and positive pathergy test) are hallmarks of BS which unequivocally occur in BS cases, regardless of their disease clusters. 61 This strongly raises the possibility of a common/shared pathogenetic component among the BS disease clusters. Venn analysis performed on the DEG lists of the M versus C, O versus C, and V versus C class comparison analyses of our study displayed that, the intersection set of these three lists contained the two genes, CLEC12A and IFI27, which are already discussed ( Figure 4). When we consider that the oral and genital areas and the skin have their unique and heavily crowded microbial floras, and the microbial breaches occurring at these sites, are initially and primarily confronted with components of the innate immune system (e.g., neutrophil granulocytes), the presence of the genes CLEC12A and IFI27, in the intersection of M versus C, O versus C, and V versus C class comparisons, makes good sense. Oguz et al. performed a similar Venn analysis in their study and interestingly found the same intersection set to be empty (i.e., none shared DEG between M vs. C, O vs. C, and V vs. C class comparisons). 5 Oguz et al. presented this finding as an important evidence of the heterogeneity at the molecular level among BS disease clusters. 5 The gene set enrichment analyses of our study yielded distinct results in different BS subgroups. As can be seen in Table 7, GO terms titled "Type I interferon signaling pathway," "Coagulation," and "Response to injury" gained special importance in mucocutaneous BS cases. "Type I interferon signaling pathway" and "Response to injury" categories are essentially innate immunity-related titles. What is striking here is that in mucocutaneous BS cases, who are accepted to be at the "mild" end of the BS disease spectrum, any processes related to the adaptive immunity did not show significant enrichment. As previously mentioned, today, BS is accepted as a complex inflammatory condition which is triggered by an exaggerated/aberrant innate immune response and is sustained by adaptive immune responses. 62 Consistent with our interferon (type I, specifically interferon alpha) signaling pathway finding, interferon signal activation were also reported in two previous BS studies by Puccetti et al. and Tulunay et al. 20,22 Coagulation was another significant GO term which drew attention and deserved a mention in the mucocutaneous BS subgroup. Puccetti et al. also showed the "Coagulation" category among the enriched GO categories in their study. 22 Although the prothrombotic state observed in cases of BS has been well-described in the literature, the molecular mechanisms responsible for this occurrence still await clarification. 63 Currently, neutrophil leukocytes' ability of "neutrophil extracellular trap" (NET) generation and thereby thrombosis formation, is increasingly emphasized in the BS literature. 64,65 When the genes which are both present in the DEG sets and also in the GO terms with the titles "Coagulation," "Blood coagulation," and "Hemostasis" are examined, C1QBP, F13A1, H3F3A, ITGA2B, and TREML1 (in alphabetical order) are noticed (Supporting Information: 7 File). At least three of these genes (i.e., H3F3A, ITGA2B, and TREML1) are currently reported to be among the genes involved in NET formation. 66,67 Even in the case of mucocutaneous BS cases, who are thought to be at the "mild" end of the BS disease spectrum, we believe that, the presence of findings related to NET formation and accompanying "immunothrombosis" may shed light on the development of the well-known prothrombotic state of BS. Finally, another GO term that showed enrichment in our mucocutaneous BS subgroup was "Response to injury." We believe that, the frequent and recurrently occurrence of mucosal surface and skin lesions in mucocutaneous BS cases makes this finding reasonable.
When gene set enrichment analyses of the ocular and vascular BS subgroups are reviewed, in addition to the GO terms such as "Immune response," "Leukocyte migration," and "Leukocyte activation" which refer to immune responses in general, GO terms such as "Adaptive immune response," "Lymphocyte activation," "IL-2 production," "Lymphocyte differentiation," and "T cell mediated immunity" which are specifically related to the adaptive immune response were found to show significant enrichment (Table 7). In the case of ocular and vascular BS, which are thought to be at the "severe" end of the BS disease spectrum, tissue damage occurs more severely and in a long standing manner, which may cause display of novel antigenic determinants from these injured "self" tissues, and thereby stimulate the patients' adaptive immune system further. [68][69][70][71][72] In three other genome wide-expression studies of BS by Tulunay et al., Okuzaki et al., and Puccetti et al., findings supporting the contribution of an adaptive immune response were also evident. [20][21][22] The findings of the gene set enrichment analyses of our study which we briefly mentioned above, can be wrapped up as "an immune-mediated disorder with innate and adaptive immune responses contributing to it, which displays an innate immunity predominance in its "mild" forms, whereas adaptive immunity is in front in its "severe" forms." This statement seems to be in harmony with the current pathogenetic mechanism definition of BS which goes as follows: "A complex genetic background leading to a proinflammatory, innate-immune system derived activation perpetuated by adaptive immune responses against environmental and autoantigens." 62,73 Like every other scientific study, our study has its own limitations. One of these limitations is about the transcriptome profiling technology implemented in our research. While transcriptome profiling can be performed by hybridization or next-generation sequencing based (RNA-seq) methodologies and we have implemented a microarray, therefore a hybridization based methodology, RNA-seq has well known advantages when compared with microarrays. Just to make a brief mention of these advantages, we should point that, RNA-seq enables detection of biologically relevant genetic variants (e.g., any gene fusions, single nucleotide variants including polymorphisms or mutations, indels, alternatively spliced transcripts, and specifically, functionally different isoforms), quantification of gene expression across a wider dynamic range with absolute values, performing analysis with a low total RNA, obtaining larger DEG sets with a higher sensitivity, and identification of the rare and low-abundance transcripts compared to microarray experiments. There are also a few points to mention, regarding the design of the research. First and foremost, it would be a better practice to view and interpret our findings while bearing in mind that they belong to a Turkish BS population. Because of major ethical concerns related to the potential threatening consequences of discontinuing their therapeutic schemes, every BS case enrolled in our study continued his/her pharmacological therapy, and this should be noted as another limitation of our study. When contrasted with similar other studies in the literature, the total number of BS cases present in our study is seemingly high. Nevertheless, the lack of BS patients with involvements of relatively uncommon organ systems (i.e., gastrointestinal, central nervous, and musculoskeletal systems) may be listed as an additional limitation of our study. Thus, we believe that it is important to plan and conduct new studies with large numbers of treatment-naive BS cases. Still another important point to remember is that, although we have searched for gene expression differences observed in BS patients, we did not obtain any information about the mechanisms responsible for the observed gene expression differences. Both epigenetic control, in the form of DNA methylation or histone modification variations, and certain single nucleotide polymorphisms (SNPs), located in the upstream and downstream transcriptional control sequences of the respective genes may well be responsible for the observed expression differences. This situation requires planning for further epigenetic or SNP (expression quantitative trait loci) analyses, which will seek to document epigenetic and genetic variants that affect the expression levels of these genes. It is also essential that the findings of our study should be validated in another Turkish BS patient cohort.
A supplement to "Discussion" section can be found in Supporting Information: 8 File.

| CONCLUSION
This comparative gene-expression profiling study of Turkish BS cases revealed a couple of important findings regarding the immunopathogenesis of BS. First of all, three genes, CLEC12A, IFI27, and CLC, appeared to be potentially instrumental in BS immunopathogenesis and these genes may be of value for therapeutic targeting and animal model development purposes. The authors of the study believe that, at least in the case of Turkish BS patients, novel targeted therapy drugs specifically "targeting" CLEC12A, CLC, and IFI27 genes/proteins may prove to be of value for therapeutic purposes. It was also shown that BS patients displayed distinct gene expression profiles and molecular disease mechanisms in different BS clinical phenotypes. A significant consequence of this finding appeared as a loss of information with the single group analysis of BS patients of different disease clusters. The authors believe that the nomenclature as the "Behçet syndrome" should be preferentially utilized and future research should take into account the molecular level heterogeneity of the distinct BS disease clusters. New studies enrolling treatment naive BS patients will be of great value and will add vital information to the topic.